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Mechanistic Assessment of the Effect of Omeprazole on the In Vivo Pharmacokinetics of Itraconazole in Healthy Volunteers

  • Ahmad Y. AbuhelwaEmail author
  • Stuart Mudge
  • Richard N. Upton
  • David J. R. Foster
Original Research Article

Abstract

Background and Objective

SUBA-itraconazole and Sporanox are two oral formulations of itraconazole. Drug–drug interactions with omeprazole have been previously reported; however, mechanistic understanding of the pharmacological and physiological interactions of omeprazole with orally administered itraconazole within a population modeling paradigm is lacking. The objective of this analysis was to mechanistically describe and quantify the effect of omeprazole on the pharmacokinetics of itraconazole and its major metabolite, hydroxyitraconazole from the SUBA itraconazole and Sporanox formulations.

Methods

An in vitro–in vivo (IVIV) pharmacokinetic model of itraconazole and hydroxyitraconazole was developed including data from an omeprazole interaction study with SUBA itraconazole. Meta-models of gastric pH for healthy subjects and subjects receiving omeprazole were integrated into the IVIV model to capture omeprazole-mediated gastric pH changes on itraconazole dissolution and absorption.

Results

Omeprazole influenced the kinetics of itraconazole through altering the dissolution and absorption due to the pH-dependent solubility of itraconazole, inhibition of efflux transporters, and inhibiting the metabolism of itraconazole and hydroxyitraconazole. The model-predicted population effects of omeprazole on itraconazole from SUBA-itraconazole were to increase the area under the concentration–time curve (AUC0–24) and maximum concentration (Cmax) by 35 and 31%, respectively, and to decrease AUC0–24 and Cmax from Sporanox by 68 and 76%, respectively.

Conclusion

Unlike SUBA itraconazole, which requires basic pH for itraconazole release, the omeprazole-induced pH-mediated reduction in Sporanox dissolution overrides any increased exposure from the drug–drug interaction at hepatic metabolizing enzymes or efflux transporters. The model presented here is the most complete quantitative description of the pharmacokinetics of itraconazole and hydroxyitraconazole currently available.

Notes

Acknowledgements

AYA is supported at the School of Pharmacy and Medical Sciences at the University of South Australia by a Science and Industry Endowment Fund STEM + Business Fellowship of the Commonwealth Scientific and Industrial Research Organisation. The Australian Centre for Pharmacometrics is an initiative of the Australian Government as part of the National Collaborative Research Infrastructure Strategy.

Compliance with Ethical Standards

Funding

All pharmacokinetic studies of Sporanox and SUBA-itraconazole used in the analysis were sponsored by Mayne Pharma International, Salisbury South, South Australia, Australia.

Conflict of Interest

SM is an employee at Mayne Pharma. DJRF, RNU and AYA have acted as paid consultants for Mayne Pharma International, Salisbury South, South Australia, Australia.

Ethical Approval

All oral pharmacokinetic studies were conducted by Mayne Pharma International, Salisbury South, South Australia, Australia, in accordance with the ICH Guidelines for Good Clinical Practice, the Declaration of Helsinki on the ethical conduct of medical research, and applicable regulatory requirements.

Informed Consent

Each subject provided written informed consent before study participation.

Supplementary material

13318_2018_519_MOESM1_ESM.pdf (467 kb)
Supplementary material 1 (PDF 467 kb)

References

  1. 1.
    Grant SM, Clissold SP. Itraconazole: a review of its pharmacodynamic and pharmacokinetic properties and therapeutic use in superfecial and systemic mycoses. Drugs. 1989;37(3):310–44.CrossRefGoogle Scholar
  2. 2.
    Kim RB. Drugs as P-glycoprotein substrates, inhibitors, and inducers. Drug Metab Rev. 2002;34(1–2):47–54.CrossRefGoogle Scholar
  3. 3.
    Abuhelwa AY, Mudge S, Hayes D, Upton RN, Foster DJ. Population in vitro–in vivo correlation model linking gastrointestinal transit time, pH, and pharmacokinetics: itraconazole as a model drug. Pharm Res. 2016;33(7):1782–94.CrossRefGoogle Scholar
  4. 4.
    Abuhelwa AY, Foster DJ, Mudge S, Hayes D, Upton RN. Population pharmacokinetic modeling of itraconazole and hydroxyitraconazole for oral SUBA-itraconazole and sporanox capsule formulations in healthy subjects in fed and fasted states. Antimicrob Agents Chemother. 2015;59(9):5681–96.CrossRefGoogle Scholar
  5. 5.
    Abuhelwa AY, Mudge S, Upton RN, Foster DJR. Population in vitro–in vivo pharmacokinetic model of first-pass metabolism: itraconazole and hydroxy-itraconazole. J Pharmacokinet Pharmacodyn. 2018;45(2):181–97.CrossRefGoogle Scholar
  6. 6.
    Abuhelwa AY, Foster DJ, Upton RN. A quantitative review and meta-models of the variability and factors affecting oral drug absorption-part I: gastrointestinal pH. AAPS J. 2016;18(5):1309–21.CrossRefGoogle Scholar
  7. 7.
    Abuhelwa AY, Foster DJ, Upton RN. A quantitative review and meta-models of the variability and factors affecting oral drug absorption-part II: gastrointestinal transit time. AAPS J. 2016;18(5):1322–33.CrossRefGoogle Scholar
  8. 8.
    Wilde MI, McTavish D. Omeprazole: an update of its pharmacology and therapeutic use in acid-related disorders. Drugs. 1994;48(1):91–132.CrossRefGoogle Scholar
  9. 9.
    Rang H, Dale M, Ritter J, Flower R, Henderson G. Rang and Dale’s Pharmacology 6th. London: Elsevier Co; 2007.Google Scholar
  10. 10.
    Pauli-Magnus C, Rekersbrink S, Klotz U, Fromm MF. Interaction of omeprazole, lansoprazole and pantoprazole with P-glycoprotein. Naunyn Schmiedebergs Arch Pharmacol. 2001;364(6):551–7.CrossRefGoogle Scholar
  11. 11.
    Li W, Zeng S, Yu L-S, Zhou Q. Pharmacokinetic drug interaction profile of omeprazole with adverse consequences and clinical risk management. Ther Clin Risk Manag. 2013;9:259.Google Scholar
  12. 12.
    Ogawa R, Echizen H. Drug-drug interaction profiles of proton pump inhibitors. Clin Pharmacokinet. 2010;49(8):509–33.CrossRefGoogle Scholar
  13. 13.
    European Medicines Agency (EMEA). Note for guidance on good clinical practice (CPMP/ICH/135/95). Step 5: consolidated guideline, including post step 4 errata. London: EMEA; 1996.Google Scholar
  14. 14.
    World Medical Association declaration of Helsinki. Recommendations guiding physicians in biomedical research involving human subjects. JAMA. 1997;277(11):925–6.CrossRefGoogle Scholar
  15. 15.
    Beal S, Sheiner LB, Boeckmann A, Bauer RJ. NONMEM user’s guides, Part V. (1989–2009). Ellicott City: Icon Development Solutions; 2009.Google Scholar
  16. 16.
    Holford, N.: Wings for NONMEM Version 7.30 for NONMEM 7.3. 2015. (2015)Google Scholar
  17. 17.
    Core Team R. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2014.Google Scholar
  18. 18.
    Wickham H. ggplot2: elegant graphics for data analysis. New York: Springer; 2009.CrossRefGoogle Scholar
  19. 19.
    Wickham H. plyr—the split-apply-combine strategy for data analysis. J Stat Softw. 2011;40(1):1–29.CrossRefGoogle Scholar
  20. 20.
    Wickham H. Scales: scale functions for graphics. 2014. http://CRAN.R-project.org/package=scales
  21. 21.
    Mandema JW, Verotta D, Sheiner LB. Building population pharmacokinetic-pharmacodynamic models. I. models for covariate effects. J Pharmacokinet Biopharm. 1992;20(5):511–28.CrossRefGoogle Scholar
  22. 22.
    Gan K, Geus W, Lamers C, Heijerman H. Effect of omeprazole 40 mg once daily on intraduodenal and intragastric pH in H. pylori-negative healthy subjects. Dig Dis Sci. 1997;42(11):2304–9.CrossRefGoogle Scholar
  23. 23.
    Wan X, Wang W, Liu J, Tong T. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Med Res Methodol. 2014;14(1):135.CrossRefGoogle Scholar
  24. 24.
    Ette EI. Stability and performance of a population pharmacokinetic model. J Clin Pharmacol. 1997;37(6):486–95.CrossRefGoogle Scholar
  25. 25.
    Naidu M, Shobha J, Dixit V, Kumar A, Kumar TR, Sekhar KR, et al. Effect of multiple dose omeprazole on the pharmacokinetics of carbamazepine. Drug Invest. 1994;7(1):8–12.CrossRefGoogle Scholar
  26. 26.
    Christians U, Schmidt G, Bader A, Lampen A, Schottmann R, Linck A, et al. Identification of drugs inhibiting the in vitro metabolism of tacrolimus by human liver microsomes. Br J Clin Pharmacol. 1996;41(3):187–90.CrossRefGoogle Scholar
  27. 27.
    Maguire M, Franz T, Hains DS. A clinically significant interaction between tacrolimus and multiple proton pump inhibitors in a kidney transplant recipient. Pediatr Transplant. 2012;16(6):E217–20.CrossRefGoogle Scholar
  28. 28.
    Collett A, Tanianis-Hughes J, Carlson GL, Harwood MD, Warhurst G. Comparison of P-glycoprotein-mediated drug–digoxin interactions in Caco-2 with human and rodent intestine: relevance to in vivo prediction. Eur J Pharm Sci. 2005;26(5):386–93.CrossRefGoogle Scholar
  29. 29.
    Oosterhuis B, Jonkman J, Andersson T, Zuiderwijk P, Jedema J. Minor effect of multiple dose omeprazole on the pharmacokinetics of digoxin after a single oral dose. Br J Clin Pharmacol. 1991;32(5):569–72.CrossRefGoogle Scholar
  30. 30.
    Jaruratanasirikul S, Sriwiriyajan S. Effect of omeprazole on the pharmacokinetics of itraconazole. Eur J Clin Pharmacol. 1998;54(2):159–61.CrossRefGoogle Scholar
  31. 31.
    Lohitnavy M, Lohitnavy O, Thangkeattiyanon O, Srichai W. Reduced oral itraconazole bioavailability by antacid suspension. J Clin Pharm Ther. 2005;30(3):201–6.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Australian Centre for Pharmacometrics and Sansom Institute, School of Pharmacy and Medical SciencesUniversity of South AustraliaAdelaideAustralia
  2. 2.Mayne Pharma InternationalSalisbury SouthAustralia

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